Assignment (ownership) text data (no images).

Contains bibliographic (front page) information and a representative drawing (if applicable) for each trademark registration or trademark application published that week. Incluides a list of cancelled and renewed registrations.

Contains bibliographic (front page) information and a representative drawing (if applicable) for each trademark registration or trademark application published that week. Incluides a list of cancelled and renewed registrations.

The Trademark Image Search API (beta) allows searching Trademark Images using various attributes like feature, accuracy, metricspaces and candidates. This API also allows searching Trademark documents using various metadata attributes like Specimen Description, Filing Description, Filing Basis, Owner's Name, Street Address, etc.

The Trademark Status and Document Retrieval (TSDR) API allows you to make programmatic requests for trademark case status, documents, and images. Beginning on October 2, 2020, you will need an API key to download bulk data from TSDR using the TSDR API. Using API keys will help optimize usage of our TSDR system, which will help enable users like yourself to better access the information you need from TSDR. The below resources will provide you with more information on using the TSDR API.

Contains detailed information on 7.0 million trademark applications filed with or registrations issued by the USPTO between 1870 and 2020.

Contains detailed information on 786,931 assignments and other transactions recorded at the USPTO between 1952 and 2020 and involving 1,491,485 million unique trademark properties.

This dataset includes the position data of a two-dimensional gantry system experiment in which the G-code commands for the gantry were transmitted through a wireless communications link. The testbed is composed of four main components related to the operation of the gantry system. These components are the gantry system, the Wi-Fi network, the RF channel emulator, and the supervisory computer. In the experimental study, we run a scenario in which the gantry tool moves sequentially between four positions and has a preset dwell at each of the positions.

Materials discovery and development necessarily begins with the preparation and identification of product phase(s). Crystalline compounds can be identified by their characteristic diffraction patterns using X-rays, neutrons, and or electrons. An estimated 20,000 X-ray diffractometers and a comparable number of electron microscopes are used daily in materials research and development laboratories for this purpose.

This tool calculates metrics for investment analysis documented in NIST Advanced manufacturing Series 200-5. It calculates net present value, internal rate of return, and payback period along with executing sensitivity analysis using Monte Carlo techniques. The tool helps to identify the most economical projects/investments. For instance, it could be used to identify the most economical heating and cooling system or it might be used to rank a set of potential investments.